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Route Optimization of Multimodal Transport Considering Regional Differences under Carbon Tax Policy

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  • Liqing Gao

    (School of Economics and Management, Taiyuan University of Technology, Taiyuan 030000, China
    Shanxi Key Laboratory of Data Factor Innovation and Economic Decision Analysis, Taiyuan 030000, China)

  • Miaomiao Zhan

    (School of Economics and Management, Taiyuan University of Technology, Taiyuan 030000, China)

Abstract

Environmental sustainability is receiving growing global attention, making the development of low-carbon and green transportation increasingly important. Low-carbon policies offer significant advantages in incentivizing energy conservation and reducing emissions in the transportation sector; however, it is vital to consider the impacts of regional differences on the implementation effect of low-carbon policies. This paper explores multimodal transportation route optimization under a carbon tax policy. First, a bi-objective route optimization model is constructed, with the goal of minimizing total transportation cost and time, while accounting for uncertain demand, fixed departure schedules, and regional differences. Trapezoidal fuzzy numbers are used to represent uncertain demand, and a fuzzy adaptive non-dominated sorting genetic algorithm is designed to solve the bi-objective optimization model. The algorithm is then tested on differently sized networks and on real-world transportation networks in eastern and western China to validate its effectiveness and to assess the impacts of regional differences. The experimental results show the following. (1) When considering transportation tasks at different network scales, the proposed fuzzy adaptive non-dominated sorting genetic algorithm outperforms the NSGA-II algorithm, achieving minimum differences in percentages of cost and time of 9.25% and 7.72%, respectively. (2) For transportation tasks assessed using real-world networks in eastern and western China, an increase in the carbon tax rate significantly affects carbon emissions, costs, and time. The degree of carbon emission reduction varies depending on the development of the regional transportation network. In the more developed eastern region, carbon emissions are reduced by up to 44.17% as the carbon tax rate increases. In the less developed western region, the maximum reduction in carbon emissions is 14.37%. The carbon tax policy has a more limited impact in the western region compared to the eastern one. Therefore, formulating differentiated carbon tax policies based on local conditions is an effective way to maximize the economic and environmental benefits of multimodal transportation.

Suggested Citation

  • Liqing Gao & Miaomiao Zhan, 2025. "Route Optimization of Multimodal Transport Considering Regional Differences under Carbon Tax Policy," Sustainability, MDPI, vol. 17(13), pages 1-24, June.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:5743-:d:1684844
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    References listed on IDEAS

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    1. Caiyi Wu & Yinggui Zhang & Yang Xiao & Weiwei Mo & Yuxie Xiao & Juan Wang, 2024. "Optimization of Multimodal Paths for Oversize and Heavyweight Cargo under Different Carbon Pricing Policies," Sustainability, MDPI, vol. 16(15), pages 1-23, August.
    2. Archetti, Claudia & Peirano, Lorenzo & Speranza, M. Grazia, 2022. "Optimization in multimodal freight transportation problems: A Survey," European Journal of Operational Research, Elsevier, vol. 299(1), pages 1-20.
    3. Lin Li & Qiangwei Zhang & Tie Zhang & Yanbiao Zou & Xing Zhao, 2023. "Optimum Route and Transport Mode Selection of Multimodal Transport with Time Window under Uncertain Conditions," Mathematics, MDPI, vol. 11(14), pages 1-25, July.
    4. Xu Zhang & Fei-Yu Jin & Xu-Mei Yuan & Hai-Yan Zhang, 2021. "Low-Carbon Multimodal Transportation Path Optimization under Dual Uncertainty of Demand and Time," Sustainability, MDPI, vol. 13(15), pages 1-18, July.
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